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Intro to Data Analysis

Utah Valley University - BIOL3100

Course Syllabus

Course file repository

Shared Course Notes

(Anyone with link can edit)

Exams GitHub Repository (Exams will be uploaded at the appropriate times)

The philosophy of this course

R for Data Science Website

Collection of beginner R resources

Table of Contents

Week 1 | Week 5 | Week 9 | Week 13

Week 2 | Week 6 | Week 10 | Week 14

Week 3 | Week 7 | Week 11 | Week 15

Week 4 | Week 8 | Week 12 | Week 16

The Command Line, File Paths, Git

Week 1

Topics:

  • Installing Software | Command-line | Git version control

Assignments

  • Read: What is Git all about?
  • Install Git, R, and R-Studio on your laptop (part of Assignment 1)
  • Be ready to explain what Git, R, and R-Studio are.
  • Do Assignment 1 and upload a link to your new GitHub account to Canvas.
  • Take a look at this document to see where this class is going
  • Go through ALL the resources below. I put them here for a reason. Most are short web resources or videos (some that I made).

Resources

Practice

  • Make 10 more separate changes and commits to your README.md file and push each one to GitHub
  • Close and open your command line terminal 10 times
  • Open your command line terminal and navigate to your new personal GitHub repository for this course (Data_Course_LASTNAME) / Navigate back to your desktop / From your Desktop (without using “cd”) display the contents of Data_Course_LASTNAME/README.md onto your computer screen.
  • Please view this short video clip from “Karate Kid” (Seriously)
    • When I tell you to close and open your command line 10 times, it’s not because I hate you.
    • It’s because I, too, have had to learn this stuff from scratch
    • It’s because I know that repetition is crucial to learning this, especially at the beginning
    • And it’s because if you don’t spend the time to do this stuff over and over now, by week 6 you will be drowning and helpless.
    • When I say “push 10 separate commits to your GitHub repo,” what I’m actually saying is “Show me ‘Paint the Fence’!”
    • Because very soon, Mr. Miyagi will be attacking you with things like “Error in url[i] = paste(df[,2], gsub(” “,”_“, : object of type ‘closure’ is not subsettable”

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Week 2

Topics

  • File paths | Pipes | Redirection | Wildcards | Essential Unix Commands | Parameters

Assignments

Resources

Practice

  • Exercise 1
  • Exercise 2
  • Shell find exercise
  • Pick some random files in our Data/ directory and practice (a bunch of times) using the following commands (with various flags and linking them with pipes):
    • head
    • tail
    • wc
    • ls
    • sort
    • uniq
  • Practice using wildcards (*) to show the contents of random files
    • Pick a few random files in a directory and try to write a wildcard expression that shows ONLY those files (wash, rinse, repeat)
  • find out what the following shell commands do and how to use them (then practice using them):
    • cp
    • mv

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Getting to Know R

Week 3

Topics

  • R Data types and conversions | Reading and Writing Files | Packages and Projects

Assignments

  • Watch this video on how to set up your personal Git Directory and R-Projects for completing assignments
  • Read this chapter on what a “package” is in R
  • Read this chapter on R-Projects (We will ALWAYS work from within R-Projects from now on)
  • Do Assignment 3 (We will start this one together during live class)
  • Do Assignment 4

Resources

Practice

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Week 4

Topics

  • Logical Operations | Subsetting | “Grammar of Graphics” ggplot Intro

Assignments

  • Read through the materials in the Resources section below
  • Make sure you have the following packages installed if you don’t already:
    • tidyverse
    • carData
    • RColorBrewer
    • colorblindr This one is “special” and not found on CRAN so click the link for install instructions.
  • Assignment 5

  • Exam 1 (Link at top of page)

Resources

Practice

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Visualizing a Data Set

Week 5

Topics

  • ggplot | patchwork | ggforce

Assignments

Resources

Practice

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Clean and Transform Data

Week 6

Topics

  • Tidy Data | dplyr verbs | tidyr verbs

Assignments

Resources

Practice

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Week 7

Topics

Assignments

  • Read This Handout
  • Read This Paper
  • Create a validated Excel Spreadsheet for data collection for the experiment we design in class
  • Exam 2

Resources

Practice

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Getting More From R

Week 8

Topics

  • Writing Functions | Conditional Execution | source()

Assignments - Watch this video from Jenny Bryan about debugging

Resources

Practice

  • Write a function that returns the min, max, and mean of any set of real numbers
  • Write a function that takes a data frame and returns a new data frame with one random column removed
  • Write a function that takes a data frame… if there are more than 3 columns, your function should return the column names as-is; if there are 3 or fewer columns, your function should return the column names in reverse order.
  • Write a useful function that you might want to use in the future (your choice)
  • Put all of these functions into a new R script and save it in your main data course repository
  • In a new empty R script, call your functions with source() and test them out

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Model Building and Testing

Week 9

Topics

  • Building and Testing Models

Assignments

Resources

Practice

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Week 10

Topics

  • More models | Statistical Tests

Assignments

Resources

Practice

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Communicating Your Results

Week 11

Topics

  • R-Markdown | Reproducible Reports

Assignments

Resources

Practice

  • Using the resources above, generate a markdown document that analyzes the “iris” data set and push it to a new GitHub repository named Iris_Markdown
  • Play with options and code to create a document that looks good and presents your analysis and results clearly
  • This is similar to Assignment_9, but I’m asking for a brand new “Iris_Markdown” repository that is self-contained.

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Week 12

Topics

  • Proper Project Organization | Collaboration

Assignments

  • Peer evaluation of Assignment 9 (Organization, Portability, Accuracy, Understandablity)
  • Exam 3

Resources

Practice

  • Peer evaluations of Iris_Markdown repositories (from last week); Clean them up and make them more organized

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Putting it all together

Week 13

Topics

  • Data Analysis from raw to report

Assignments

  • We will work together in class to do a complete analysis in real-time

Resources

Practice

  • Analyze the “esoph” data set and generate a markdown report

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Week 14

Topics

  • Building a website with GitHub and R-Markdown

Assignments

  • Work on Final Project
  • Create a GitHub Personal Website
  • Upload a brief CV and the updated (improved) html of Assignment 9 to your new website

Resources

Practice

  • Go through my course website repository (link above) and try to relate the code there to the html version of the website your internet browser is displays

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Week 15

Topics

  • TBD

Assignments

  • Work on Final Project

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Week 16

Topics

  • TBD

Assignments

  • Exam 4 (Redo any previous exam to replace it’s score)

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‘Luck is statistics taken personally.’ – Penn Jillette